#9 The Ultimate Guide to Nailing Your Data Science Application - Pt. 1 - DODS

🔍 Are you eager to land your dream job? Look no further! Join us as we unveil the essential steps every aspiring data scientist 𝑺𝑯𝑶𝑼𝑳𝑫 𝑻𝑨𝑲𝑬 𝑩𝑬𝑭𝑶𝑹𝑬 venturing into the job market. If you like our podcast, please consider leaving a review on Spotify, subscribe on YouTube, and leave a comment and/or 👍! This would help us a lot ♥️ In this episode, we delve into the ‼️essential steps aspiring data scientists must take before applying for 👔positions in the field. Drawing from personal experiences, mentoring sessions, and consultations, we've crafted a comprehensive guide to help you navigate the complexities of the data science landscape. In this episode, we'll delve deep into: ▪️ 𝐏𝐫𝐞𝐩𝐚𝐫𝐢𝐧𝐠 𝐟𝐨𝐫 𝐒𝐮𝐜𝐜𝐞𝐬𝐬: Discover what steps you need to take before even thinking about hitting that "apply" button. ▪️ 𝐒𝐭𝐫𝐚𝐭𝐞𝐠𝐢𝐜 𝐀𝐩𝐩𝐫𝐨𝐚𝐜𝐡: Learn the essential strategies for crafting a standout application that catches the eye of recruiters.  ▪️ 𝐂𝐡𝐨𝐨𝐬𝐢𝐧𝐠 𝐭𝐡𝐞 𝐑𝐢𝐠𝐡𝐭 𝐅𝐢𝐭: Explore the crucial factors to consider when selecting the perfect company for your career aspirations. Here's a sneak peek at what's in store (unpaid advertisement, personal recommendations): @Kaggle: https://www.kaggle.com @GitHub: https://github.com @Kununu: https://www.kununu.com @Glassdor: https://www.glassdoor.de/index.htm @Linkedin: https://www.linkedin.com ML algorithms discussed in the episode: Liner regression Ridge, Lasso, Elastic Net regression Logistic regression Decision tree Random forest SVD k-NN DBSCAN K-means Naive Bayes

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